Overview

Dataset statistics

Number of variables11
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory86.1 KiB
Average record size in memory88.1 B

Variable types

NUM10
BOOL1

Warnings

X0 has unique values Unique
X1 has unique values Unique
X2 has unique values Unique
X3 has unique values Unique
X4 has unique values Unique
X5 has unique values Unique
X6 has unique values Unique
X7 has unique values Unique
X8 has unique values Unique
X9 has unique values Unique

Reproduction

Analysis started2020-12-15 20:03:43.222184
Analysis finished2020-12-15 20:04:06.986719
Duration23.76 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

X0
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03617510703
Minimum-3.529962031
Maximum2.903643112
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:04:07.081156image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.529962031
5-th percentile-1.565408941
Q1-0.5924804365
median0.04109809653
Q30.7030744527
95-th percentile1.612154468
Maximum2.903643112
Range6.433605142
Interquartile range (IQR)1.295554889

Descriptive statistics

Standard deviation0.9685584744
Coefficient of variation (CV)26.77417025
Kurtosis0.04813013612
Mean0.03617510703
Median Absolute Deviation (MAD)0.6460248894
Skewness-0.07175880738
Sum36.17510703
Variance0.9381055183
MonotocityNot monotonic
2020-12-15T21:04:07.293440image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.250552527910.1%
 
0.253830296510.1%
 
-1.54885949510.1%
 
0.584183010810.1%
 
-0.00260281386210.1%
 
0.0881515515510.1%
 
-1.603188110.1%
 
1.34467446410.1%
 
-1.12510817410.1%
 
0.0792493123410.1%
 
-1.01795897610.1%
 
0.205499909410.1%
 
2.44987505910.1%
 
-0.572291116810.1%
 
1.29396543310.1%
 
-0.417770277710.1%
 
-0.434305729710.1%
 
1.67048298510.1%
 
0.880325046910.1%
 
0.346668138910.1%
 
-1.01425100410.1%
 
-2.196541310.1%
 
0.428304991110.1%
 
-0.575728068310.1%
 
0.773257975510.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.52996203110.1%
 
-3.05875277810.1%
 
-2.62788653510.1%
 
-2.61314026710.1%
 
-2.53428693810.1%
 
-2.48065710110.1%
 
-2.4541981810.1%
 
-2.41852245810.1%
 
-2.41558930310.1%
 
-2.39350705410.1%
 
ValueCountFrequency (%) 
2.90364311210.1%
 
2.77643835610.1%
 
2.66185441210.1%
 
2.44987505910.1%
 
2.39653709610.1%
 
2.33765686710.1%
 
2.32873114610.1%
 
2.24095181910.1%
 
2.23275884910.1%
 
2.18279899410.1%
 

X1
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02269071028
Minimum-3.454914175
Maximum2.877431864
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:04:07.530094image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.454914175
5-th percentile-1.709996969
Q1-0.6871900872
median0.03488696419
Q30.7218353737
95-th percentile1.7250739
Maximum2.877431864
Range6.332346039
Interquartile range (IQR)1.409025461

Descriptive statistics

Standard deviation1.036177197
Coefficient of variation (CV)45.66526054
Kurtosis-0.1705912972
Mean0.02269071028
Median Absolute Deviation (MAD)0.7109283275
Skewness-0.07015982215
Sum22.69071028
Variance1.073663183
MonotocityNot monotonic
2020-12-15T21:04:07.750307image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.381362056910.1%
 
-0.762851781510.1%
 
1.0500317710.1%
 
0.0330934475810.1%
 
0.372624243410.1%
 
0.88697894510.1%
 
-3.09831989510.1%
 
1.56808907510.1%
 
0.771864471110.1%
 
-0.17210057110.1%
 
0.920610423710.1%
 
1.53114978310.1%
 
-0.440642553910.1%
 
-0.0622132610210.1%
 
-1.31825412510.1%
 
0.338664329710.1%
 
-0.158974165410.1%
 
-0.0250703285110.1%
 
-1.39800137810.1%
 
-1.3566257310.1%
 
-0.645163960810.1%
 
-0.644309218410.1%
 
1.90376714510.1%
 
-0.794093490610.1%
 
0.398390978510.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.45491417510.1%
 
-3.09831989510.1%
 
-2.83653604310.1%
 
-2.6284100310.1%
 
-2.60505305510.1%
 
-2.59361606810.1%
 
-2.52768491710.1%
 
-2.52026029110.1%
 
-2.42154871710.1%
 
-2.41245016810.1%
 
ValueCountFrequency (%) 
2.87743186410.1%
 
2.7459291510.1%
 
2.7333266610.1%
 
2.71228347510.1%
 
2.58934343210.1%
 
2.52781658310.1%
 
2.50868426110.1%
 
2.45436682910.1%
 
2.36613925710.1%
 
2.34725987810.1%
 

X2
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04000169062
Minimum-2.658544078
Maximum2.904039628
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:04:07.977295image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2.658544078
5-th percentile-1.62910889
Q1-0.6363335221
median0.03471042024
Q30.7327370366
95-th percentile1.672010633
Maximum2.904039628
Range5.562583706
Interquartile range (IQR)1.369070559

Descriptive statistics

Standard deviation0.9848569606
Coefficient of variation (CV)24.62038342
Kurtosis-0.2995433761
Mean0.04000169062
Median Absolute Deviation (MAD)0.6853682445
Skewness-0.007138712882
Sum40.00169062
Variance0.9699432329
MonotocityNot monotonic
2020-12-15T21:04:08.376415image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.523813292110.1%
 
-1.51549467110.1%
 
-0.882990936310.1%
 
0.152037169510.1%
 
-0.441974960810.1%
 
0.766235948410.1%
 
-2.15830329510.1%
 
1.72511422810.1%
 
-0.362208151510.1%
 
-0.490098403810.1%
 
0.318144102610.1%
 
-0.215692656510.1%
 
-0.757833816710.1%
 
-0.0945113156510.1%
 
-0.540080561310.1%
 
-0.962627440910.1%
 
0.38168950510.1%
 
-0.586479819210.1%
 
-0.769177001710.1%
 
-1.69364960810.1%
 
-0.365491478210.1%
 
-0.302876120810.1%
 
1.23163803210.1%
 
0.678848854110.1%
 
0.124807083810.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.65854407810.1%
 
-2.4654185610.1%
 
-2.38292483810.1%
 
-2.37011008810.1%
 
-2.30484680610.1%
 
-2.30034515110.1%
 
-2.28054478510.1%
 
-2.26577955610.1%
 
-2.20920211910.1%
 
-2.15830329510.1%
 
ValueCountFrequency (%) 
2.90403962810.1%
 
2.88358654910.1%
 
2.60530377510.1%
 
2.53516932410.1%
 
2.51777597310.1%
 
2.36645705710.1%
 
2.33988601310.1%
 
2.32707876210.1%
 
2.3001218110.1%
 
2.27650415710.1%
 

X3
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.05686023266
Minimum-3.900279198
Maximum3.718247323
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:04:08.614266image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.900279198
5-th percentile-1.750046242
Q1-0.6994475426
median-0.06964331895
Q30.6792935125
95-th percentile1.505627351
Maximum3.718247323
Range7.618526521
Interquartile range (IQR)1.378741055

Descriptive statistics

Standard deviation0.991279533
Coefficient of variation (CV)-17.43361725
Kurtosis0.08084992251
Mean-0.05686023266
Median Absolute Deviation (MAD)0.6861226757
Skewness-0.09002852965
Sum-56.86023266
Variance0.9826351125
MonotocityNot monotonic
2020-12-15T21:04:08.842468image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.368374537210.1%
 
-0.958655840210.1%
 
-1.35631688210.1%
 
0.223381085410.1%
 
0.778444550310.1%
 
0.17730919310.1%
 
0.239647510410.1%
 
-1.06901836310.1%
 
-0.295414306510.1%
 
1.09026870610.1%
 
1.1526329710.1%
 
-0.0330442899210.1%
 
-0.791186565110.1%
 
1.2446002210.1%
 
1.01110450110.1%
 
1.12003589710.1%
 
-0.684782533410.1%
 
0.107612711910.1%
 
-1.19929195610.1%
 
1.50558172510.1%
 
0.515640029710.1%
 
0.878918349310.1%
 
0.615642144810.1%
 
0.183799693610.1%
 
-0.675121998210.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.90027919810.1%
 
-3.20428378610.1%
 
-3.00845023610.1%
 
-2.65454514510.1%
 
-2.63012529810.1%
 
-2.57380784110.1%
 
-2.49962875610.1%
 
-2.49712033710.1%
 
-2.40884523810.1%
 
-2.39558719510.1%
 
ValueCountFrequency (%) 
3.71824732310.1%
 
2.72642607110.1%
 
2.62975243910.1%
 
2.59168439210.1%
 
2.54912896510.1%
 
2.39527041710.1%
 
2.37462261810.1%
 
2.16192455910.1%
 
2.15836431910.1%
 
2.13829198610.1%
 

X4
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.01753751986
Minimum-2.907909178
Maximum3.47781797
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:04:09.081145image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2.907909178
5-th percentile-1.696673528
Q1-0.6758154613
median0.02260265286
Q30.6405664033
95-th percentile1.65036256
Maximum3.47781797
Range6.385727148
Interquartile range (IQR)1.316381865

Descriptive statistics

Standard deviation1.003263869
Coefficient of variation (CV)-57.20671321
Kurtosis0.02247398775
Mean-0.01753751986
Median Absolute Deviation (MAD)0.654687197
Skewness0.002651006024
Sum-17.53751986
Variance1.006538391
MonotocityNot monotonic
2020-12-15T21:04:09.300536image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.562180033210.1%
 
-1.07179941810.1%
 
-0.0335002277510.1%
 
-0.159717393910.1%
 
0.913673705210.1%
 
0.417599722110.1%
 
0.646517231910.1%
 
-0.321165987410.1%
 
-0.414520905210.1%
 
0.33803302610.1%
 
-0.895704711410.1%
 
-1.24115480510.1%
 
-0.265550536810.1%
 
-0.80289510710.1%
 
0.624340169810.1%
 
1.54131470910.1%
 
-2.39014328610.1%
 
0.235772485610.1%
 
-0.0060983272710.1%
 
-0.21993861910.1%
 
0.185352650710.1%
 
0.134710879910.1%
 
-0.819266159410.1%
 
-0.610421645210.1%
 
1.15273972110.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.90790917810.1%
 
-2.7772618910.1%
 
-2.73140406510.1%
 
-2.64874709710.1%
 
-2.53261914810.1%
 
-2.50802537710.1%
 
-2.46518783410.1%
 
-2.44778839510.1%
 
-2.43473270910.1%
 
-2.39014328610.1%
 
ValueCountFrequency (%) 
3.4778179710.1%
 
2.96815607210.1%
 
2.74685450610.1%
 
2.72240705310.1%
 
2.64736795310.1%
 
2.56431394910.1%
 
2.46965108810.1%
 
2.44992593510.1%
 
2.44680589810.1%
 
2.32205548210.1%
 

X5
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04592513521
Minimum-3.169120695
Maximum3.135007727
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:04:09.527446image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.169120695
5-th percentile-1.644028261
Q1-0.7165921184
median0.07055769946
Q30.7871155577
95-th percentile1.748240084
Maximum3.135007727
Range6.304128422
Interquartile range (IQR)1.503707676

Descriptive statistics

Standard deviation1.056446968
Coefficient of variation (CV)23.00367681
Kurtosis-0.2118258732
Mean0.04592513521
Median Absolute Deviation (MAD)0.7422704837
Skewness0.01068411069
Sum45.92513521
Variance1.116080196
MonotocityNot monotonic
2020-12-15T21:04:09.730576image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.660084066110.1%
 
1.76803751910.1%
 
-0.351370267810.1%
 
-0.475133337410.1%
 
-0.542426791110.1%
 
-1.52736616210.1%
 
0.115399651610.1%
 
0.626699645110.1%
 
-0.916043407910.1%
 
0.602774021110.1%
 
0.0360054428810.1%
 
-0.431740819110.1%
 
-0.926397079610.1%
 
1.02728415310.1%
 
-0.676426797810.1%
 
-0.810380055510.1%
 
1.51967565810.1%
 
-1.89153550410.1%
 
-0.816950687610.1%
 
-0.232492495410.1%
 
1.23762964110.1%
 
0.450358189810.1%
 
0.550432758110.1%
 
1.24209373310.1%
 
0.71399308410.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.16912069510.1%
 
-2.87391433210.1%
 
-2.71241195110.1%
 
-2.64433354510.1%
 
-2.5921220710.1%
 
-2.57232500910.1%
 
-2.53531808710.1%
 
-2.53362304310.1%
 
-2.50766553210.1%
 
-2.33190504110.1%
 
ValueCountFrequency (%) 
3.13500772710.1%
 
3.05694114910.1%
 
3.04959227410.1%
 
2.96945311910.1%
 
2.72721768810.1%
 
2.67747739510.1%
 
2.65337407510.1%
 
2.63474072510.1%
 
2.49118111510.1%
 
2.4547852810.1%
 

X6
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.02026970446
Minimum-2.808630984
Maximum3.068605616
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:04:09.952887image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2.808630984
5-th percentile-1.618317935
Q1-0.7285149616
median-0.0361030851
Q30.6584155156
95-th percentile1.666243705
Maximum3.068605616
Range5.8772366
Interquartile range (IQR)1.386930477

Descriptive statistics

Standard deviation1.002567874
Coefficient of variation (CV)-49.46139574
Kurtosis-0.1169608649
Mean-0.02026970446
Median Absolute Deviation (MAD)0.6925788125
Skewness0.1447236668
Sum-20.26970446
Variance1.005142342
MonotocityNot monotonic
2020-12-15T21:04:10.303494image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.726133420610.1%
 
-2.43761536610.1%
 
-2.67652312310.1%
 
1.14998090610.1%
 
-1.61656465110.1%
 
-0.571685888310.1%
 
0.853125743910.1%
 
-1.63831672810.1%
 
-0.8094603410.1%
 
-0.0917741798410.1%
 
0.00510955006810.1%
 
-0.332781422410.1%
 
-0.508969170410.1%
 
-0.563146474910.1%
 
-1.96859654310.1%
 
-0.172540076810.1%
 
-0.261369581210.1%
 
0.540851740610.1%
 
0.77031786510.1%
 
0.51367494110.1%
 
-1.05608925510.1%
 
0.239714386410.1%
 
-0.0587477665610.1%
 
-0.282318034510.1%
 
0.582095755110.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.80863098410.1%
 
-2.67652312310.1%
 
-2.48661692210.1%
 
-2.48653234810.1%
 
-2.45247349310.1%
 
-2.44885415810.1%
 
-2.43761536610.1%
 
-2.37665337610.1%
 
-2.31628426410.1%
 
-2.30014366610.1%
 
ValueCountFrequency (%) 
3.06860561610.1%
 
3.00486407610.1%
 
2.8740606110.1%
 
2.77716315510.1%
 
2.74226719610.1%
 
2.72202078210.1%
 
2.60254966110.1%
 
2.49309339210.1%
 
2.48936159310.1%
 
2.47544508710.1%
 

X7
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.003336859767
Minimum-2.857213454
Maximum2.730076056
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:04:10.523863image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2.857213454
5-th percentile-1.569695383
Q1-0.6521426565
median-0.007780284704
Q30.6104804795
95-th percentile1.664598059
Maximum2.730076056
Range5.58728951
Interquartile range (IQR)1.262623136

Descriptive statistics

Standard deviation0.9646646771
Coefficient of variation (CV)-289.0935623
Kurtosis0.001637013441
Mean-0.003336859767
Median Absolute Deviation (MAD)0.6390412541
Skewness0.04651018394
Sum-3.336859767
Variance0.9305779393
MonotocityNot monotonic
2020-12-15T21:04:10.726682image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.0710048268410.1%
 
1.0717677710.1%
 
-1.1986600310.1%
 
-1.3820291210.1%
 
0.0675325620210.1%
 
0.589454193510.1%
 
-0.835038287410.1%
 
-1.48500116210.1%
 
0.752197742710.1%
 
-0.00927784791410.1%
 
1.83416505410.1%
 
1.60620140310.1%
 
0.887211551210.1%
 
-1.39098944110.1%
 
0.481481910210.1%
 
0.118798458710.1%
 
-0.42929489510.1%
 
-0.550482422910.1%
 
0.10388035210.1%
 
-1.29067454710.1%
 
1.30320233610.1%
 
1.15081352910.1%
 
-0.1986944210.1%
 
-0.316006750610.1%
 
-0.202522174210.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.85721345410.1%
 
-2.82278741210.1%
 
-2.79320985210.1%
 
-2.58124464910.1%
 
-2.51801802810.1%
 
-2.46444301410.1%
 
-2.42794324210.1%
 
-2.32692109410.1%
 
-2.2743887110.1%
 
-2.2390923510.1%
 
ValueCountFrequency (%) 
2.73007605610.1%
 
2.69312015110.1%
 
2.55321964710.1%
 
2.46451848610.1%
 
2.42586294210.1%
 
2.42511208310.1%
 
2.41322844510.1%
 
2.40271810.1%
 
2.39962098710.1%
 
2.32723206310.1%
 

X8
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.02444034464
Minimum-4.012536941
Maximum3.233648569
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:04:10.963744image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-4.012536941
5-th percentile-1.773826408
Q1-0.6976564022
median0.008086757642
Q30.6279008492
95-th percentile1.63227781
Maximum3.233648569
Range7.24618551
Interquartile range (IQR)1.325557251

Descriptive statistics

Standard deviation1.014931314
Coefficient of variation (CV)-41.52688227
Kurtosis0.1136583604
Mean-0.02444034464
Median Absolute Deviation (MAD)0.6828686427
Skewness-0.1209985335
Sum-24.44034464
Variance1.030085573
MonotocityNot monotonic
2020-12-15T21:04:11.189332image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.0444673745210.1%
 
-0.134867451110.1%
 
0.425445614310.1%
 
-0.121679805610.1%
 
-1.31629095710.1%
 
-0.169510813810.1%
 
2.02420882610.1%
 
0.646802694310.1%
 
-2.22514700110.1%
 
-1.83910401210.1%
 
-0.255073060110.1%
 
-0.323960972510.1%
 
-1.75220919110.1%
 
0.993827113310.1%
 
-0.90306794610.1%
 
-1.08387844510.1%
 
-0.505560854710.1%
 
-0.389268268710.1%
 
-0.49191313710.1%
 
0.916069363910.1%
 
0.703598355910.1%
 
-1.04413731910.1%
 
-0.749705808210.1%
 
-0.112750609810.1%
 
-0.655639967210.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-4.01253694110.1%
 
-3.37128897210.1%
 
-3.17887785510.1%
 
-2.59443351910.1%
 
-2.59260696510.1%
 
-2.58194939210.1%
 
-2.52649994210.1%
 
-2.42750920510.1%
 
-2.39833860810.1%
 
-2.39462873110.1%
 
ValueCountFrequency (%) 
3.23364856910.1%
 
3.19415183610.1%
 
2.81224094610.1%
 
2.64398787810.1%
 
2.47026793510.1%
 
2.45382487310.1%
 
2.37862859210.1%
 
2.36577038210.1%
 
2.32066075710.1%
 
2.28647359610.1%
 

X9
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02137370559
Minimum-2.83227657
Maximum3.828046539
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:04:11.428650image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2.83227657
5-th percentile-1.577639182
Q1-0.669830103
median0.033783295
Q30.6955293405
95-th percentile1.596559435
Maximum3.828046539
Range6.660323109
Interquartile range (IQR)1.365359443

Descriptive statistics

Standard deviation0.9789793307
Coefficient of variation (CV)45.80297631
Kurtosis-0.05391121565
Mean0.02137370559
Median Absolute Deviation (MAD)0.6849220952
Skewness0.005368658421
Sum21.37370559
Variance0.9584005299
MonotocityNot monotonic
2020-12-15T21:04:11.638578image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.242823716710.1%
 
-1.70393815410.1%
 
0.260898164210.1%
 
-2.01455251110.1%
 
-0.103880701510.1%
 
0.777857879310.1%
 
1.05721234510.1%
 
-0.789351043710.1%
 
0.645781499610.1%
 
0.285040270710.1%
 
1.08594021910.1%
 
-0.909844605110.1%
 
2.61307753810.1%
 
0.708647644310.1%
 
0.860366335710.1%
 
1.93149614310.1%
 
0.298196295810.1%
 
1.28012969410.1%
 
1.65342984710.1%
 
0.82922513210.1%
 
0.259759218510.1%
 
1.01997033210.1%
 
-0.0432888336310.1%
 
1.13107794210.1%
 
0.102186316210.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.8322765710.1%
 
-2.69066451610.1%
 
-2.61659657610.1%
 
-2.55631108210.1%
 
-2.50391292310.1%
 
-2.39860731710.1%
 
-2.32933323910.1%
 
-2.32603668110.1%
 
-2.24372082310.1%
 
-2.22935831810.1%
 
ValueCountFrequency (%) 
3.82804653910.1%
 
3.17304997410.1%
 
2.85695826610.1%
 
2.61307753810.1%
 
2.52602503410.1%
 
2.48988530210.1%
 
2.46180130510.1%
 
2.34580853910.1%
 
2.33240488310.1%
 
2.22244025610.1%
 

y
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
1
500 
0
500 
ValueCountFrequency (%) 
150050.0%
 
050050.0%
 
2020-12-15T21:04:11.816422image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Interactions

2020-12-15T21:03:44.065954image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:44.281686image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:44.490859image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:44.699973image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:44.921729image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:45.138037image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:45.351419image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:45.552400image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:45.756590image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:45.962496image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:46.173644image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:46.378388image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:46.593057image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:03:48.200913image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:03:48.837901image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:49.062452image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:49.283265image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:49.483570image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:03:51.380734image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:51.600512image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:51.820718image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:52.051475image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:52.280159image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:52.501818image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:52.727536image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:52.924960image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:53.133224image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:53.340157image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:53.566768image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:53.784700image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:54.135684image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:54.365278image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:54.575008image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:54.803237image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:55.030496image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:55.243192image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:55.463827image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:55.671259image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:55.885234image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:56.095212image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:56.309092image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:56.519354image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:56.740177image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:56.964898image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:57.194688image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:57.410015image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:57.627633image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:57.834216image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:58.062876image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:58.282677image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:58.500803image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:58.733844image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:58.953045image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:59.168906image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:59.374267image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:59.585074image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:03:59.793920image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:00.003217image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:00.224399image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:00.603511image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:00.810644image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:01.022521image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:01.240092image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:01.460405image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:01.683105image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:01.911790image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:02.128904image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:02.341396image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:02.554000image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:02.772705image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:03.005919image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:03.249041image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:03.466710image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:03.693439image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:03.922629image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:04.150451image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:04.371989image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:04.584757image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:04.812062image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:05.029763image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:05.249679image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:05.475191image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:05.697971image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:05.930741image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2020-12-15T21:04:11.931882image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-15T21:04:12.220564image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-15T21:04:12.504516image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-15T21:04:12.788268image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-12-15T21:04:06.307737image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:06.815364image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

X0X1X2X3X4X5X6X7X8X9y
00.2997050.227769-0.5232590.2168490.7520890.2080550.6080860.477166-0.713713-0.4881870
11.344850-0.0103690.403361-0.8658600.512502-1.445484-0.8262030.705370-0.6153560.0606130
20.2545631.2284610.881334-0.206295-2.508025-0.9769750.1712791.1730590.707441-1.5606851
30.188666-1.2571141.964045-1.170420-0.9806290.5969990.6121831.9835292.030201-0.1990101
42.159570-0.1246140.1609430.888493-0.0350341.0957191.0679960.5241970.2748531.1310781
5-0.662696-0.2120861.4873691.168802-1.9170132.4911810.3839742.151849-1.8618180.9346861
60.8857160.8011230.3350640.5006061.0034900.1961680.0326560.7913820.2232710.5361321
71.870022-0.105476-0.1502480.6570410.625853-0.511580-0.5826350.5135930.8105281.2356311
8-0.622326-0.743988-0.3622081.374686-1.4794070.0062830.8355590.1626541.0586191.4399141
9-1.238467-0.769899-1.977112-1.8937760.0607170.185895-0.748074-0.8234591.612379-0.6092360

Last rows

X0X1X2X3X4X5X6X7X8X9y
9900.870396-2.1466860.5702180.5060690.224685-0.507285-0.5634981.5781671.1005740.2697051
9911.389649-1.0450710.4185970.4389741.0259760.7772500.8981770.227768-1.2586960.2215410
9920.6159531.995559-0.860948-0.914020-0.939549-0.028105-0.777112-0.140599-0.9623130.8116120
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